Artificial intelligence is rapidly reshaping how software is developed. A 2024 Stack Overflow survey of 65,000 developers found that 76% already use or plan to use AI tools for tasks like code generation, debugging, refactoring, and testing. Major tech companies are embracing the trend: Google CEO Sundar Pichai reports that AI writes over a quarter of the company’s code, while IBM relies on AI to translate legacy COBOL into Java language. This shift hints at a future where AI increasingly propels efficiency and innovation in coding.
What is Business Logic in Coding?
Business logic governs the rules and decision-making processes tied to an organization’s unique operations or domain requirements. It dictates how an application should handle various inputs—like validating user data, calculating prices, or managing workflows—based on well-defined criteria. Unlike presentation logic (user interfaces) or infrastructure logic (databases and servers), business logic focuses on the “why” behind each action, aligning the application with real-world policies and constraints.
Here are three examples demonstrating how business logic applies in different scenarios:
- Business Tax Rules: Varying regional tax brackets and frequent regulatory changes make tax calculations highly complex, particularly for companies operating across multiple jurisdictions.
- Product Configuration & Pricing: Multiple rules may dictate product attributes, bundled discounts, and promotions, further complicated by changing costs or currency rates.
- Loan Eligibility: Lenders rely on factors like credit history and debt-to-income ratio to determine loan amounts, and these criteria can differ greatly from one institution to another.
Excel is the Platform of Choice for Subject Matter Experts to Implement Business Logic
Despite AI’s gains, Excel remains the go-to for many business users due to its accessibility and robust formula library. Features like formula auditing and the newer LAMBDA function allow subject matter experts to debug and test calculations quickly, ensuring accurate rules without waiting on full development cycles. This agility is especially valuable when market conditions or regulations change, enabling rapid updates to pricing models, tax rules, or eligibility criteria.
Implementing Excel-Based Business Logic in Applications
While AI-driven tools may someday fully convert complex Excel logic into code, current solutions often fall short of capturing every rule and exception. Specialized platforms like SpreadsheetWeb already fill this gap, transforming Excel workbooks into web applications or APIs that retain complete fidelity to original business rules. By eliminating extensive manual coding and providing standardized APIs, these platforms offer a more reliable path to integrating Excel-based logic into broader systems.
Ultimately, business logic remains one of the most complex aspects of application development, and Excel continues to be an essential tool for building and iterating on that logic. Until AI matures enough to handle intricate, domain-specific calculations with minimal oversight, platforms that bridge spreadsheets and enterprise apps will remain the most practical solution for maintaining speed, accuracy, and adaptability in software projects.
Originally published at https://www.linkedin.com.
